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In this paper, we propose a novel sampling control framework based on the emulation technique where the sampling error is regarded as an auxiliary input to the emulated system. Utilizing the supremum norm of sampling error, the design of…

Optimization and Control · Mathematics 2022-05-02 Lijun Zhu , Zhiyong Chen

Many real-world mission-critical applications require continual online learning from noisy data and real-time decision making with a defined confidence level. Probabilistic models and stochastic neural networks can explicitly handle…

Disordered Systems and Neural Networks · Physics 2022-06-01 Sourav Dutta , Georgios Detorakis , Abhishek Khanna , Benjamin Grisafe , Emre Neftci , Suman Datta

Modeling and simulating the protein folding process overall remains a grand challenge in computational biology. We systematically investigate end-to-end quantum algorithms for simulating various protein dynamics with effects, such as…

Quantum Physics · Physics 2025-04-17 Zhenning Liu , Xiantao Li , Chunhao Wang , Jin-Peng Liu

Umbrella sampling is an efficient method for the calculation of free energy changes of a system along well-defined reaction coordinates. However, when multiple parallel channels along the reaction coordinate or hidden barriers in directions…

Methodology · Statistics 2015-06-16 Mingjun Yang , Lijiang Yang , Yiqin Gao , Hao Hu

We describe a novel coarse-grained simulation method for modelling the dynamics of globular macromolecules, such as proteins. The macromolecule is treated as a continuum that is subject to thermal fluctuations. The model includes a…

Computational Physics · Physics 2015-06-11 Robin Oliver , Daniel J. Read , Oliver G. Harlen , Sarah A. Harris

Molecular dynamics (MD) simulation is widely used to study protein conformations and dynamics. However, conventional simulation suffers from being trapped in some local energy minima that are hard to escape. Thus, most computational time is…

Quantitative Methods · Quantitative Biology 2022-04-28 Hao Tian , Xi Jiang , Sian Xiao , Hunter La Force , Eric C. Larson , Peng Tao

We derived a number of numerical methods to treat biomolecular systems with multiple time scales. Based on the splitting of the operators associated with the slow-varying and fast-varying forces, new multiple time-stepping (MTS) methods are…

Numerical Analysis · Mathematics 2015-01-15 Chao Liang , Xiaolan Yuan , Xiantao Li

Molecular dynamics simulations are widely used across chemistry, physics, and biology, providing quantitative insight into complex processes with atomic detail. However, their limited timescale of a few microseconds is a significant…

Chemical Physics · Physics 2025-04-10 Ofir Blumer , Barak Hirshberg

We investigate the use of compressive sampling for networked feedback control systems. The method proposed serves to compress the control vectors which are transmitted through rate-limited channels without much deterioration of control…

Systems and Control · Computer Science 2016-11-15 Masaaki Nagahara , Daniel E. Quevedo , Takahiro Matsuda , Kazunori Hayashi

Parallel tempering, also known as replica exchange sampling, is an important method for simulating complex systems. In this algorithm simulations are conducted in parallel at a series of temperatures, and the key feature of the algorithm is…

Probability · Mathematics 2012-06-14 Paul Dupuis , Yufei Liu , Nuria Plattner , J. D. Doll

Many recently introduced enhanced sampling techniques are based on biasing coarse descriptors (collective variables) of a molecular system on the fly. Sometimes the calculation of such collective variables is expensive and becomes a…

Computational Physics · Physics 2015-09-01 Marco Jacopo Ferrarotti , Sandro Bottaro , Andrea Pérez-Villa , Giovanni Bussi

Inverse protein folding, the process of designing sequences that fold into a specific 3D structure, is crucial in bio-engineering and drug discovery. Traditional methods rely on experimentally resolved structures, but these cover only a…

Biomolecules · Quantitative Biology 2023-11-27 Igor Melnyk , Aurelie Lozano , Payel Das , Vijil Chenthamarakshan

We present a procedure for enhanced sampling of molecular dynamics simulations through informed stochastic resetting. Many phenomena, such as protein folding and crystal nucleation, occur over time scales that are inaccessible in standard…

Biased sampling of collective variables is widely used to accelerate rare events in molecular simulations and to explore free energy surfaces. However, computational efficiency of these methods decreases with increasing number of collective…

Chemical Physics · Physics 2017-04-05 Shalini Awasthi , Nisanth N. Nair

Detecting conformational transitions in molecular systems is key to understanding biological processes. Here, we investigate the force variance in single-molecule pulling experiments as an indicator of molecular folding transitions. We…

Statistical Mechanics · Physics 2023-09-13 Marc Rico , Felix Ritort

Accurate force fields are essential for reliable molecular simulations. These models are refined against quantum mechanical calculations and experimental measurements, which are subject to random and systematic errors. Bayesian Inference of…

Chemical Physics · Physics 2025-11-04 Robert M. Raddi , Vincent A. Voelz

The current capacity of computers makes it possible to perform simulations of small systems with portable, explicit-solvent potentials achieving high degree of accuracy. However, simplified models must be employed to exploit the behaviour…

Biomolecules · Quantitative Biology 2015-06-18 R. Capelli , C. Paissoni , P. Sormanni , G. Tiana

From the point of view of statistical mechanics, a full characterisation of a molecular system requires the experimental determination of its possible states, their populations and the respective interconversion rates. Well-established…

Computational Physics · Physics 2020-06-02 Z. Faidon Brotzakis , Michele Vendruscolo , Peter. G. Bolhuis

A model system inspired by recent experiments on the dynamics of a folded protein under the influence of a sinusoidal force is investigated and found to replicate many of the response characteristics of such a system. The essence of the…

Soft Condensed Matter · Physics 2015-09-30 Craig Fogle , Joseph Rudnick , David Jasnow

To address the computational challenges of ab initio molecular dynamics and the accuracy limitations of empirical force fields, the introduction of machine learning force fields has proven effective in various systems including metals and…

Soft Condensed Matter · Physics 2023-12-18 Junbao Hu , Liyang Zhou , Jian Jiang